Two-dimensional imager with solid-state auto-focus

ABSTRACT

An imaging system having a solid-state auto focusing system advantageously images broadband light reflected from an object to be imaged using a lens objective having chromatic aberration, which focuses different colors of light at different focal planes. Using the color information in the focal planes in conjunction with an object distance determined by a range finder, a luminance plane is constructed that has a focused image of the object. The system provides the focused image of the object without the use of any moving parts.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of the following application whichis incorporated by reference in its entirety, U.S. ProvisionalApplication No. 61/468,401, entitled “TWO-DIMENSIONAL IMAGER WITHSOLID-STATE AUTO-FOCUS”, filed Mar. 28, 2011.

BACKGROUND

Conventional two-dimensional area imagers employ auto-focus devices toaccommodate a wide range of reading distances. The auto-focus devicesare typically based upon either a moving lens or a moving image planethat physically changes the focal plane of the optical system. Theseauto-focus devices with moving parts can suffer from several drawbackssuch as wear-and-tear, increased drain on batteries when implemented inportable devices, and a need for recalibration of the moving parts.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A depicts the focal planes for three representative colors, blue,green, and red for a lens with dispersion that causes the refractiveindex to decrease with increasing wavelength.

FIG. 1B depicts the focal planes for a lens combination that causes therefractive index to increase with increasing wavelength for threerepresentative colors, blue, green, and red.

FIG. 2A shows a Bayer filter, and FIGS. 2B-2D show the sensor pixels inthe imaging array for the filtered colors.

FIG. 3 is a flow diagram illustrating an example process of autofocusingan imaging system by constructing a luminance plane.

FIG. 4 is a conceptual graph of example curves of contributions of highspatial frequencies of different color planes to the luminance plane.

FIG. 5 is a graph obtained from computer simulations that shows examplecurves of the modulation transfer function (MTF) for different colorplanes as a function of object distance.

FIG. 6 shows a block diagram of an imager used to read barcodes or othermachine-readable symbols.

FIG. 7 shows a block diagram of a solid-state auto-focus subsystem of animager used to read barcodes or other machine-readable symbols.

DETAILED DESCRIPTION

Chromatic aberration is a lens distortion that arises due to dispersion,i.e., a variation of the refractive index of the lens material as afunction of wavelength. As a result, the lens focuses differentwavelengths of light at different focal distances. An optical readerthat uses a lens with chromatic aberration in conjunction with threedifferent colored lights that fire sequentially can improve the depth offocus of the reader. However, expensive electronics are needed toimplement this type of reader.

A two-dimensional imaging system having a solid-state auto focusingsystem is described. The system advantageously uses chromatic aberrationinherent in optical lenses with a broadband light source to focusdifferent colors of light at different focal planes. Additionally, thedistance from the imaging system to the object to be imaged can bedetermined by an independent light beam. By using the distanceinformation with color information in different focal planes, aluminance plane can be constructed and used to auto focus the imagingsystem without any moving parts.

Various aspects and examples of the invention will now be described. Thefollowing description provides specific details for a thoroughunderstanding and enabling description of these examples. One skilled inthe art will understand, however, that the invention may be practicedwithout many of these details. Additionally, some well-known structuresor functions may not be shown or described in detail, so as to avoidunnecessarily obscuring the relevant description.

The terminology used in the description presented below is intended tobe interpreted in its broadest reasonable manner, even though it isbeing used in conjunction with a detailed description of certainspecific examples of the technology. Certain terms may even beemphasized below; however, any terminology intended to be interpreted inany restricted manner will be overtly and specifically defined as suchin this Detailed Description section.

Typically, a white light source, such as a white light emitting diode(LED), is used in an optical reader for illuminating a barcode or othermachine-readable symbol to be read, and a lens focuses light receivedfrom the target object. With conventional imaging systems, it isdesirable to minimize the amount of chromatic aberration in the lens.The techniques to be presented below advantageously use the chromaticaberration in the objective lens to reconstruct a luminance plane forauto-focusing the imaging system.

A lens with inherent material dispersion focuses different wavelengthcomponents of white light at different focal planes. With conventionaltypes of glasses that are used for making lenses, the dispersion causesthe refractive index to decrease with increasing wavelength. Thus, for apositive lens, the longer wavelengths of light are focused farther awayfrom the lens. FIG. 1A depicts a lens 110 and corresponding focal planesfor three representative colors, blue (121) (shortest wavelengths),green (122), and red (123) (longest wavelengths). White light LEDs emitmore power in the longer wavelength (blue) portion of the spectrum thanin the shorter wavelength (red) portion of the spectrum, thus thematerial dispersion of a typical lens results in the higher power bluelight being focused in the near field. However, it is beneficial todirect more light power into the far field in order to maintain a moreeven power distribution in the scan range because light power decreaseswith distance. Thus, it is desirable to reverse the chromatic aberrationto focus the blue light in the far field.

One method of reversing chromatic aberration is to use two or morelenses which together result in negative chromatic aberration but stillmaintains a positive focal length. In one example, a first lens is madefrom crown glass, and a second lens is made from flint glass. Thecombination of the lenses reverses the order in which the wavelengths oflight are focused. In another example, a hologram lens can be used asthe second lens. FIG. 1B depicts a combination lens that comprises anobjective lens 150 and a hologram lens 155. The objective lens 150 has adispersion that causes chromatic aberration. The hologram lens 155 isused to apply dispersion to the light to be imaged that is opposite insign to the dispersion of the objective lens 150. The order of the focalplanes for the combination lens for the three representative colors blue(163), green (162), and red (161) is reversed as compared to the orderof the focal planes shown in FIG. 1A. In either of the above examples,the dispersion of the second lens combined with the objective lens 150should be large enough to spread the focal planes of the red and bluewavelengths, where the red wavelengths are focused more strongly thanthe blue wavelengths. However, the combined dispersion of the lensescannot be too large otherwise there will be gaps in the reading betweenthe color planes which will prevent the machine-readable symbols frombeing accurately read.

Because the objective lens combination has sufficient chromaticaberration to separate the focal planes of the different wavelengths oflight, a color filter array can be used advantageously with a whitelight source to analyze the different wavelengths of light reflectedfrom the target object to autofocus the system. One non-limiting exampleof a color filter array is a Bayer filter 205, as shown in FIG. 2A. TheBayer filter is a square grid of red, green, and blue color filters,where each filter overlays a single pixel or photosensor of atwo-dimensional imaging array. In the first row of the Bayer filter,blue and green filters alternate, and in the second row of the Bayerfilter, green and red filters alternate. The pattern in the first tworows of the filter is repeated through the rest of the rows of thefilter. Essentially, the Bayer filter is made up of grids of 2×2sub-filters repeated over the entire filter, and each 2×2 sub-filter hastwo green filters, one blue filter, and one red filter. Other colorfilter arrays having a different number of color filters can also beused.

The raw data for the red focal plane is captured in the sensor pixelscorresponding to the red filters, as shown in FIG. 2B. Similarly, thedata for the green and blue focal planes are captured by thecorresponding sensor pixels, as shown in FIGS. 2C and 2D, respectively.Because the Bayer filter does not provide data for each color plane ateach pixel of the sensor, the missing data should be reconstructed usinga de-mosaicing algorithm. Those skilled in the art will be familiar withde-mosaicing algorithms, ranging from a simple ‘nearest-neighbor’technique to other more complex algorithms such as bi-cubic or splineinterpolation.

To accurately determine appropriate de-mosaicing parameters, a rangefinder can be used to measure the distance from the imaging system tothe target. In one embodiment, an optical aiming system, for example alaser beam that has a different axis from the main imaging optical axis,is used as a range finder. Such optical aiming systems are common insome existing imagers. As a result of parallax between the two opticalaxes, the position of the spot produced on the image by the aimingsystem can be triangulated to determine the distance from the imagingsystem to the target. Although the precision of the measurementdecreases with the square of the reading distance, it is more thansufficient to tune the de-mosaicing algorithm quite accurately,especially for imagers designed to read symbols at close range (e.g.under one meter) or even at mid-range distances. The amount of lightused to read a target ultimately limits the range of auto-focus that canbe achieved with this technique. With conventional light sources, apractical limit to the auto-focus range that can be achieved is about ameter.

One alternative to using a color filter array with wide spectrumlighting is to use a wide spectrum image sensor with differentmonochromatic or narrow wavelength band illumination sources, forexample, different color LEDs. Then de-mosaicing of the image data isnot needed, but this comes at the expense of using additional lightingsources.

FIG. 3 is a flow diagram illustrating an example process 300 of readinga machine-readable object with a solid-state auto-focusing imagingsystem. At block 305, the system determines the distance to the objectto be read. A range finder, such as a laser beam, can be used.

In one embodiment, the distance information obtained from the rangefinder can optionally be used to adjust an aperture in the opticalsystem, i.e., the aperture can be reduced for closer targets to obtainbetter resolution, while the aperture can be increased for targets atfarther distances to permit more light to be gathered.

At block 310, the system captures the raw image data for the individualcolors to be analyzed. In one example, image data for three colors canbe captured, for example, red, green, and blue using a Bayer filter, asdescribed above. However, image data for any three color planes can becaptured. Moreover, image data for more or fewer colors can be captured.Using four color planes would provide better information forauto-focusing the system, however three colors may be more easilyimplemented because there are many commonly available components thatsupport this configuration. It is desirable to capture the green imagedata because the green focal plane is very similar to the luminanceplane as a result of the sensitivity of the human eye to greenwavelengths around 555 nm. By including the green image data, an imageof the target object can be reproduced for display to a user.

At block 315, the system interpolates the image data for each capturedcolor plane by using a de-mosaicing algorithm. For example, gaps in thered or blue image data obtained with a Bayer filter can be filled-inusing a bi-linear or bi-cubic interpolation, and gaps in the green imagedata can be filled-in using an edge sensitive bi-linear interpolation.As will be appreciated by those skilled in the art, other de-mosaicingalgorithms can also be used.

Because each of the different colors is focused in a different focalplane, each of the focal planes has a different magnification. At block320, the system corrects the magnification of the images for each of thecolors such that each image of the object has the same height. The valueof the magnification is calculated using an optical design program andknown parameters for the objective lens combination.

Next, at block 325 the system determines the high and low spatialfrequencies from the image data for each color plane. All spatialfrequencies present in each color plane are classified as either a highspatial frequency or a low spatial frequency, depending on whether thefrequency is above or below a boundary frequency. In one example, theboundary frequency can be 1/3 or 1/4 of the Nyquist frequency. However,the boundary frequency can be chosen to be higher or lower. Once theboundary frequency is selected, each color plane can be decomposed andexpressed as the sum of the high frequency contributions of the colorplane and the low frequency contributions of the color plane, as shownin equations (1):

G=>G_(H)+G_(L)

R=>R_(H)+R_(L)  (1)

B=>B_(H)+B_(L),

where G, R, and B represent the raw image data for the green, red, andblue color planes, respectively, and G_(H), R_(H), B_(H) are the valuesof the high spatial frequency contributions for the green, red, and blueplanes, respectively, and G_(L), R_(L), B_(L) are the values of the lowspatial frequency contributions for the green, red, and blue planes,respectively.

One method for extracting the low spatial frequencies is to use aGaussian binomial filter which acts as a low pass filter. To extract thehigh spatial frequencies, one method is to use an unsharp mask filterwhich operates to enhance high spatial filter detail at the expense oflow spatial frequency information. Those skilled in the art will befamiliar with various other filters or methods that can be used forextracting high and/or low spatial frequencies from image data.

The color planes are decomposed into the high and low spatialfrequencies of the respective color plane because when the imagingsystem reads a barcode or other machine-readable symbol, the barcode orsymbol information is primarily high spatial frequency information.Thus, in order to auto-focus the imaging system, it is important todetermine for each color the dependence of the high spatial frequencyinformation on the distance to the target object.

Then at block 330, the system constructs a luminance plane from thecaptured image data. Color space can be defined by the YUV model, whereY is the luminance component, and U and V are the chrominance or colorcomponents. The luminance plane, or Y plane, is a linear combination ofthe high spatial frequencies and the low spatial frequencies of thethree color planes as shown in equation (2):

Y=αG_(H)+βR_(H)+γB_(H)+δG_(L)+εR_(L)+ηB_(L),  (2)

where the coefficients α, β, γ, δ, ε, and η are the respectivecontributions of the G_(H), R_(H) , B_(H), G_(L), R_(L), and B_(L) colorplanes to the luminance of the image of the target. The coefficientsvary as a function of the object distance.

The low frequency contributions from the red and blue color planes arenot as important, and in one embodiment, the coefficients ε and η thatspecify contributions for the low spatial frequencies from the red andblue planes, respectively, can be set to zero. However, the low spatialfrequencies in the green plane provide needed luminance informationbecause the green color plane is very close to the luminance plane incolor space as a result of the human eye being most sensitive to greenwavelengths near 555 nm. The coefficient δ for the low frequencycontributions from the green color plane is equal to (1−α). For astandard conversion from the RGB color plane to the YUV color plane, theconversion formula for the luminance is given by Y=0.587 G+0.299 R+0.114B, where G, R, and B are the contributions from the green, red, and blueplanes, respectively, and α=0.587, β=0.299 and γ=0.114. However, forauto-focusing the imaging system, the coefficients for α, β, and γ inequation (2) are different from the standard values and should bedetermined empirically.

One example of the dependence of the coefficients for the high spatialfrequencies of the color planes, α, β, and γ, on object distance isshown in FIG. 4. The curves for α(420), β(430) and γ(410) as a functionof object distance are shown. Note that for the far field (fartherobject distance), the coefficient β for the red color-plane is zero,while for the near field (closer object distance), the coefficient γ forthe blue color-plane is zero. These values are consistent with thediagram shown in FIG. 1B where the longer red wavelengths are focused inthe near field, and the shorter blue wavelengths are focused in the farfield. For different systems, the slopes of the curves for thecoefficients and the points at which the curves cross can vary from theexample curves shown in FIG. 4.

One way to determine how much each color plane should contribute to thetotal luminance Y is to generate computer simulations of the systemperformance for each of the color planes and analyze the contribution ofeach color plane as a function of object distance. A simulation that isa useful guide for performing the analysis of the color planecontributions is the modulation transfer function (MTF) plotted as afunction of object distance for each of the color planes. Examples ofMTF curves are shown in FIG. 5 for the blue color plane (510), the greencolor plane (520), and the red color plane (530). In one embodiment, theobject distances corresponding to the peaks of the MTF curves for thedifferent color planes can be used to adjust the curves for thecoefficients as a function of object distance. Because the coefficientsα, β, and γ are dependent upon the object distance, the distance betweenthe imaging system and the target obtained at block 305 is used todetermine the values of the coefficients for the particular object beingimaged. The corresponding coefficients are then used to construct theluminance plane for the object.

The constructed luminance plane which includes information from the highspatial frequencies of the three color planes should be sufficient torecover the target symbol being imaged. Empirically, it has beendetermined that only approximately 10% modulation transfer function isneeded to recover a bar code from the image data using this method.

Then at block 335, the system can display the luminance plane which hasa focused image of the target. Alternatively, or additionally, thesystem can analyze the luminance plane to decode the barcode or othermachine-readable symbol that has been imaged, print the luminance plane,or transmit the data for the luminance plane for further processing. Theprocess ends at block 399.

FIG. 6 shows a block diagram 600 of an imager used to read barcodes orother machine-readable symbols. An imager can include one or moreprocessors 610, memory units 620, user interface 630, auto-focus system650, radio 660, and power supply 670.

A processor 610 can be used to run imager applications. Memory 620 caninclude but is not limited to, RAM, ROM, and any combination of volatileand non-volatile memory. A power supply 670 can include, but is notlimited to, a battery. A user interface 630 can include, but is notlimited to, triggers to start and stop the imager or to initiate otherimager functions, visual displays, speakers, and communication devicesthat operate through wired or wireless communications. A radio 660includes standard components for communication. The solid stateauto-focus system 650 focuses the imager without any moving parts.

FIG. 7 shows a block diagram of the solid state auto-focus system 700.The auto-focus system 700 can include a light source 710, an objectivelens 720, image sensor 740, color filter array 750, and range finder760.

The light source 710 is used to illuminate the target object and can bea broad spectrum light source, such as a white light source. Theobjective lens 720 is any combination of optics that provides asufficiently strong chromatic aberration that focuses light havinglonger wavelengths more than light having shorter wavelengths.

The image sensor 740 captures light from a target object focused by theobjective lens 720. The color filter array 750 transmits only certainwavelengths of light such that the image sensor 740 only captures lightin a fixed wavelength range on certain pixels. The range finder 760 isused to determine the distance from the imager to the target object.

CONCLUSION

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense (i.e., to say, in thesense of “including, but not limited to”), as opposed to an exclusive orexhaustive sense. As used herein, the terms “connected,” “coupled,” orany variant thereof means any connection or coupling, either direct orindirect, between two or more elements. Such a coupling or connectionbetween the elements can be physical, logical, or a combination thereof.Additionally, the words “herein,” “above,” “below,” and words of similarimport, when used in this application, refer to this application as awhole and not to any particular portions of this application. Where thecontext permits, words in the above Detailed Description using thesingular or plural number may also include the plural or singular numberrespectively. The word “or,” in reference to a list of two or moreitems, covers all of the following interpretations of the word: any ofthe items in the list, all of the items in the list, and any combinationof the items in the list.

The above Detailed Description of examples of the invention is notintended to be exhaustive or to limit the invention to the precise formdisclosed above. While specific examples for the invention are describedabove for illustrative purposes, various equivalent modifications arepossible within the scope of the invention, as those skilled in therelevant art will recognize. While processes or blocks are presented ina given order in this application, alternative implementations mayperform routines having steps performed in a different order, or employsystems having blocks in a different order. Some processes or blocks maybe deleted, moved, added, subdivided, combined, and/or modified toprovide alternative or subcombinations. Also, while processes or blocksare at times shown as being performed in series, these processes orblocks may instead be performed or implemented in parallel, or may beperformed at different times. Further any specific numbers noted hereinare only examples. It is understood that alternative implementations mayemploy differing values or ranges.

The various illustrations and teachings provided herein can also beapplied to systems other than the system described above. The elementsand acts of the various examples described above can be combined toprovide further implementations of the invention.

Any patents and applications and other references noted above, includingany that may be listed in accompanying filing papers, are incorporatedherein by reference. Aspects of the invention can be modified, ifnecessary, to employ the systems, functions, and concepts included insuch references to provide further implementations of the invention.

These and other changes can be made to the invention in light of theabove Detailed Description. While the above description describescertain examples of the invention, and describes the best modecontemplated, no matter how detailed the above appears in text, theinvention can be practiced in many ways. Details of the system may varyconsiderably in its specific implementation, while still beingencompassed by the invention disclosed herein. As noted above,particular terminology used when describing certain features or aspectsof the invention should not be taken to imply that the terminology isbeing redefined herein to be restricted to any specific characteristics,features, or aspects of the invention with which that terminology isassociated. In general, the terms used in the following claims shouldnot be construed to limit the invention to the specific examplesdisclosed in the specification, unless the above Detailed Descriptionsection explicitly defines such terms. Accordingly, the actual scope ofthe invention encompasses not only the disclosed examples, but also allequivalent ways of practicing or implementing the invention under theclaims.

While certain aspects of the invention are presented below in certainclaim forms, the applicant contemplates the various aspects of theinvention in any number of claim forms. For example, while only oneaspect of the invention is recited as a means-plus-function claim under35 U.S.C. §112, sixth paragraph, other aspects may likewise be embodiedas a means-plus-function claim, or in other forms, such as beingembodied in a computer-readable medium. (Any claims intended to betreated under 35 U.S.C. §112, ¶6 will begin with the words “means for.”)Accordingly, the applicant reserves the right to add additional claimsafter filing the application to pursue such additional claim forms forother aspects of the invention.

1. An imaging apparatus having a solid state auto-focus, the apparatuscomprising: a broadband light source configured to illuminate an objectto be imaged; an objective lens module configured to focus the broadbandlight reflected from the object, wherein the objective lens module has achromatic aberration that separates focal planes of differentwavelengths of light; a two-dimensional image sensor configured tocapture image data of the object; a two-dimensional color filter arrayconfigured to filter light reflected from the object before reaching theimage sensor, wherein the filtering comprises transmitting only one bandof wavelengths at certain positions in the array, and at least two bandsof wavelengths are transmitted over the array; a range finder configuredto determine a distance of the object from the image sensor; and, aprocessor configured to construct a luminance plane containing an imageof the object by adding weighted high and low spatial frequencycontributions from the image data for each of the bands of wavelengths,wherein the weighting of the contributions is based at least upon thedistance of the object from the image sensor.
 2. The apparatus of claim1, wherein the color filter array is a Bayer filter, and the processoris further configured to perform a demosaicing algorithm to interpolatemissing image data not transmitted by the color filter array.
 3. Theapparatus of claim 1, wherein the chromatic aberration of the objectivelens module focuses light at longer wavelengths more strongly than lightat shorter wavelengths.
 4. The apparatus of claim 1, wherein theobjective lens module includes a hologram lens and a lens component,wherein the lens component has a first dispersion and the hologram lenshas a second dispersion, and the second dispersion is opposite in signto the first dispersion.
 5. The apparatus of claim 1, wherein theimaging apparatus further comprises a display for displaying the imageof the object in the luminance plane.
 6. The apparatus of claim 1,wherein the processor further decodes the image of the object in theluminance plane.
 7. A method of auto-focusing an imaging system, themethod comprising: focusing broadband light reflected from an object tobe imaged, wherein different wavelengths of light are focused atdifferent focal surfaces; filtering the focused light to determinecontributions of light to one or more color surfaces; capturing imagedata of the object, wherein the image data comprises the filteredfocused light; constructing a resultant surface for the captured imagedata; and, identifying the object imaged in the resultant surface,wherein the object imaged in the resultant surface is focused.
 8. Themethod of claim 7, wherein filtering the focused light comprisestransmitting only one contiguous group of wavelengths at certain spatiallocations within the image data, and at least two contiguous groups ofwavelengths are transmitted within the captured image data.
 9. Themethod of claim 7, wherein constructing the resultant surface comprises:decomposing the contributions of light to the one or more color surfacesinto high frequency components and low frequency components; determiningcontributions of the high frequency components and the low frequencycomponents for each of the one or more color surfaces to the resultantsurface.
 10. The method of claim 9, wherein determining contributions ofthe high frequency components and the low frequency components for eachof the one or more color surfaces to the resultant surface comprises:empirically obtaining data for a modulation transfer function (MTF) as afunction of object distance for the imaging system; determiningcontributions of the high frequency components and the low frequencycomponents based upon the empirical data.
 11. The method of claim 7,wherein filtering the focused light comprises: using a filter array tofilter the focused light; performing a demosaicing algorithm tointerpolate missing image data not transmitted by the filter array. 12.The method of claim 11, wherein the filter array is a Bayer filter. 13.The method of claim 7, wherein focusing the reflected light from theobject comprises focusing longer wavelength light more strongly thanshorter wavelength light.
 14. The method of claim 7, further comprisingdisplaying the image of the object in the resultant surface.
 15. Animaging apparatus having a solid state auto-focus, the apparatuscomprising: multiple narrowband light sources configured to illuminatesimultaneously an object to be imaged; a lens configured to focus lightfrom the multiple narrowband light sources reflected from the object,wherein the lens has a chromatic distortion that separates focal planesof different wavelengths of light; a sensor configured to capture imagedata of the object at the wavelengths emitted by the multiple narrowbandlight sources; a processor configured to construct a new planecontaining an image of the object by adding weighted high and lowspatial frequency components from the image data for each of the narrowbands of wavelengths.
 16. The apparatus of claim 15, wherein thechromatic distortion of the lens focuses longer wavelength light closerto the lens than shorter wavelength light.
 17. The apparatus of claim15, wherein the imaging apparatus further comprises a display fordisplaying the image of the object in the new plane.
 18. The apparatusof claim 15, wherein the processor further decodes the image of theobject in the new plane.
 19. The apparatus of claim 15, wherein the lensincludes a hologram lens and a lens component, wherein the lenscomponent has a first dispersion and the hologram lens has a seconddispersion, and the second dispersion has a different sign from thefirst dispersion.
 20. An imaging apparatus having a solid stateauto-focus, the apparatus comprising: means for focusing broadband lightreflected from an object to be imaged, wherein different wavelengths oflight are focused at different focal planes; means for filtering thefocused light to determine contributions of light to one or more colorplanes; means for receiving image data of the object, wherein the imagedata comprises the filtered focused light; means for constructing acomposite plane for the captured image data; means for determining theobject imaged in the composite plane, wherein the object imaged in thecomposite plane is focused.